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The reality of the inbox is that people subscribe to a lot more stuff than they are committed to reading. As a result, they sift through the advertising and marketing noise to find the gems--the messages they connect with and that add value to their lives.

From your initial sign up process to the content and frequency of your messaging, your most important job is showing your audience that you respect the privilege of being invited into their inbox.

Mistake 1.  Not putting a strong interdisciplinary team together. It is impossible to put together an analytics platform without understanding the needs of the customers who will use it.  Sounds simple, right?  Who wouldn’t do that?  You’d be surprised how many analytics projects are wrapped up by IT because “they think” they know the customer needs.  Not assembling the right team is clearly the biggest mistake companies make.  Many times what is on your mind (and if you’re an IT person willing to admit it) is that you are considering converting all those favorite company reports.  Your goal should not be that.  Your goal is to create a system—human engineered with customers, financial people, IT folks, analysts, and others—that give people new and exciting ways to look at information.  It should give you new insights. New competitive information.  If you don’t get the right team put together, you’ll find someone longing for the good old days and their old dusty reports.  Or worse yet, still finding ways to generate those old dusty reports. Mistake 2.  Not having the right talent to design, build, run and update your analytics system.  It is undeniable that there is now high demand for business analytics specialists.  There are not a lot of them out there that really know what to do unless they’ve been burned a few times and have survived and then built successful BA systems.  This is reflected by the fact you see so many analytics vendors offer, or often recommend, third-party consulting and training to help the organization develop their business analytic skills.  Work hard to build a three-way partnership between the vendor, your own team, and an implementation partner.  If you develop those relationships, risk of failure goes way down.

Mistake 3.  Putting the wrong kind of analyst or designer on the project. This is somewhat related to Mistake 2 but with some subtle differences.  People have different skillsets so you need to make sure the person you’re considering to put on the project is the right “kind.”  For example, when you put the design together you need both drill-down and summary models.  Both have different types of users.  Does this person know how to do both?  Or, for example, inexperience in an analyst might lead to them believing vendor claims and not be able to verify them as to functionality or time to implement. Mistake 4.  Not understanding how clean the data is you are getting and the time frame to get it clean.  Profile your data to understand the quality of your source data.  This will allow you to adjust your system accordingly to compensate for some of those issues or more importantly push data fixes to your source systems.  Ensure high quality data or your risk upsetting your customers.  If you don’t have a good understanding of the quality of your data, you could easily find yourself way behind schedule even though the actual analytics and business intelligence framework you are building is coming along fine. Mistake 5.  Picking the wrong tools.  How often do organizations buy software tools that just sit on the shelve?  This often comes from management rushing into a quick decision based on a few demos they have seen.  Picking the right analytics tools requires an in-depth understanding of your requirements as well as the strengths and weaknesses of the tools you are evaluating.  The best way to achieve this understanding is by getting an unbiased implementation partner to build a proof of concept with a subset of your own data and prove out the functionality of the tools you are considering. Bottom Line.  Think things through carefully. Make sure you put the right team together.  Have a data cleansing plan.  If the hype sounds too good to be true—have someone prove it to you.

In the past, prospects primarily accessed information about a company by interacting directly with a salesperson.

As media evolved, mass ads, events, direct mail, and more recently, email, have been the primary tools for engagement.

The balanced scorecard is one popular methodology for linking strategy, technology, and performance management. Other methodologies, such as applied information economics, combine statistical analysis, portfolio theory, and decision science in order to help firms calculate the economic value of better information. Whether you use a published methodology or develop your own approach in-house, the important point is to make sure your BI activities are keyed to generating real business value, not merely creating pretty, but useless, dashboards and reports.

1. Project Sponsorship and Governance 2. Project Management 3. Development Team (Core Team) 4. Extended Project Team

1. Project Sponsorship and Governance IT and the business should form a BI steering committee to sponsor and govern design, development, deployment, and ongoing support. It needs both the CIO and a business executive, such as CFO, COO, or a senior VP of marketing/sales to commit budget, time, and resources. The business sponsor needs the project to succeed. The CIO is committed to what is being built and how.

2. Project Management Project management includes managing daily tasks, reporting status, and communicating to the extended project team, steering committee, and affected business users. The project management team needs extensive business knowledge, BI expertise, DW architecture background, and people management, project management, and communications skills. The project management team includes three functions or members: Project development manager - Responsible for deliverables, managing team resources, monitoring tasks, reporting status, and communications. Requires a hands-on IT manager with a background in iterative development. Must understand the changes caused by this approach and the impact on the business, project resources, schedule and the trade-offs. Business advisor - Works within the sponsoring business organization. Responsible for the deliverables of the business resources on the project's extended team. Serves as the business advocate on the project team and the project advocate within the business community. Often, the business advocate is a project co-manager who defers to the IT project manager the daily IT tasks but oversees the budget and business deliverables. BI/DW project advisor - Has enough expertise with architectures and technologies to guides the project team on their use. Ensures that architecture, data models, databases, ETL code, and BI tools are all being used effectively and conform to best practices and standards.

The tag-management industry is growing rapidly, as tags are critical to gathering data about your customers.

It's the early days for tag management, but the industry is growing rapidly because it's not so much about tags, but about the bigger challenge of using digital data.

Where does tag management fit in the data picture? Here's an example someone shared with me recently: He had gone to an antivirus product's website, read the reviews, and bought the software. In the days that followed, however, he suddenly began to see banner ads from that same software maker whenever he visited CNN, ESPN, and other favorite websites. The software maker knew he had visited its website, but not that he already bought the product. They were retargeting him with banner ads at unnecessary cost and no purpose.

You cannot accept problems as handed to you in the business environment. Never allow yourself to be the analyst to whom problems are “thrown over the fence.” Engage with the people whose challenges you’re tackling to make sure you’re solving the right problem. Learn the business’s processes and the data that’s generated and saved. Learn how folks are handling the problem now, and what metrics they use (or ignore) to gauge success.

Solve the correct, yet often misrepresented, problem. This is something no mathematical model will ever say to you. No mathematical model can ever say, “Hey, good job formulating this optimization model, but I think you should take a step back and change your business a little instead.” And that leads me to my next point: Learn how to communicate.

In today’s business environment, it is often unacceptable to be skilled at only one thing. Data scientists are expected to be polyglots who understand math, code, and the plain-speak (or sports analogy-ridden speak . . . ugh) of business. And the only way to get good at speaking to other folks, just like the only way to get good at math, is through practice.

Step 3: Edit the my.cnf file

Search for the following line:[mysqld] Make sure line skip-networking is commented (or remove line) and add following line:bind-address=YOUR-SERVER-IPSo if your IP is 69.195.199.51 the entire block should look like this:[mysqld] port = 3306 socket = /var/lib/mysql/mysql.sock skip-locking key_buffer_size = 16K max_allowed_packet = 1M table_open_cache = 4 sort_buffer_size = 64K read_buffer_size = 256K read_rnd_buffer_size = 256K net_buffer_length = 2K thread_stack = 128K bind-address = 69.195.199.51 # skip-networking

Step 4: Save & RestartSave your edits by clicking on the Save button and restart MySQL by clicking RestartStep 5: Grant access to remote IP addressGo to the terminal in the control panel and log in (or connect via SSH) and connect to your MySQL database.$ mysql -u root -p mysqlGrant access to a new database If you want to add a new database called foo for user bar and remote IP 69.195.199.100 then you need to type the following commands at mysql> prompt:mysql> CREATE DATABASE foo; mysql> GRANT ALL ON foo.* TO bar@'69.195.199.100' IDENTIFIED BY 'PASSWORD';How Do I Grant Access To An Existing Database? To grant access to an existng database called foo for user bar and remote IP 69.195.199.100 type the following command At mysql> prompt for existing database, enter:mysql> GRANT ALL ON foo.* TO bar@'69.195.199.100' IDENTIFIED BY 'PASSWORD';

mysqldump -h localhost -u [MySQL user, e.g. root] -p[database password] -c --add-drop-table --add-locks --all --quick --lock-tables [name of the database] > sqldump.sql

Extract the Database

Any individual fish or pod of fish in your sea represents one lead.

Your Nemo will not be the first or the second fish that you catch. At the beginning, you will have very little information about the Nemo you would like to catch. You will start to examine your fish and create some criteria as to how Nemo should look like. In other words, you are qualifying your fish.

Lead = Any Fish in The Sea. Opportunity = Nemo

Great design, high-quality code, strong business sponsorship, accurate requirements, good project management, and thorough testing are some of the obvious requirements for successful analytics systems.

As a professional in the field, you must be able to do these things well because they form the foundation of a good analytics implementation.

Successful analytics professionals should follow a set of guiding principles.

Schema on write This is the traditional approach for Business Intelligence. A model, often dimensional, is built as part of the design process. This model is an abstraction of the complexity of the underlying systems, put in business terms. The purpose of the model is to allow the business users to interrogate the data in a way they understand.

The model is instantiated through physical database tables and the date is loaded through an ETL (extract, transform and load) process that takes data from one or more source systems and transforms it to fit the model, then loads it into the model.

The key thing is that the model is determined before the data is finally written and the users are very much guided or driven by the model in how they query the data and what results they can get from the system. The designer must anticipate the queries and requests in advance of the user asking the questions.

Secure VPN Connection terminated locally by the client. Reason 442: Failed to enable Virtual Adapter

HKLM\SYSTEM\CurrentControlSet\Services\CVirtA

regedit

1) Do bad customer experiences cause people to switch brands? In a 2011 research project conducted by CX application vendor RightNow, 89% of consumers said that yes, a bad experience has spurred them to switch brands. But in the brand-new study of business-executive perceptions that’s the subject of this column, only 49% of the surveyed executives said yes.  QUESTION: What steps do you need to take to close this dangerous perception gap? 2) While 97% of executives say CX is critical to the success of their company, and 91% say they’re committed to making their company a CX leader, only 20% would rate their own CX initiatives as “advanced,” with a dedicated CX leader in place, initial projects pushed to the optimization phase, and the overall project extended to new channels and groups . QUESTION: What are the obstacles preventing you from aligning your actions with your words? If you say it’s a “budget” issue, aren’t you really talking about strategic priorities rather than line items? 3) Most companies have a clear and direct understanding of the looming CX challenge and the powerful interaction of social media. The study found that the top two drivers for CX initiatives are (a) rising expectations from customers (59%),  and (b) the impact of social media on customers’ ability to broadcast good and bad experiences (37%). Now, even if you’re able to somehow rationalize those findings, here’s one that not even the most-accommodating executive can dismiss:

4) Being a CX laggard can cost those companies many tens of millions or even hundreds of millions of dollars in lost revenue: executives estimated that the lack of positive, consistent, and brand-relevant customer experience can cause them to lose out on a staggering 20% in annual revenue.

Worse yet, all that money’s likely to wind up in the pockets of your competitors!

In this article we explain how you can utilize the apache authentication to restrict access to you website or parts of your website.

You have to create the files .htaccess and .htpasswd. These files are protected by the server software so you can not download or view them with your web browser.

You can’t learn data visualization by memorizing a set of rules. You must understand why things work the way they do.

you must be able to think statistically

This doesn’t mean that you must learn advanced mathematics, nor can you do this work merely by learning how to use software to calculate correlation coefficients and p-values.

All of which led me to FusionCharts, which is a brilliant set of flash charts and widgets.

All I had to do was figure out how to integrate it into my app. First I had to write a function to extract the data I needed from my database and output it as correctly-formatted XML. That bit was easy so I won't bore you with it.

Next I uploaded the Flash (SWF) file for my chart into my workspace. (Tell me something: when you upload an image to your application using Apex's image uploader you refer to it by pointing at # APP_IMAGES#, so how do you think you'd refer to a file you've uploaded using Apex's file uploader? #APP_FILES#? Wrong! Illogically, all files uploaded into your application should be pointed at using the #APP_IMAGES# substitution string.)Finally, I created a dynamic PL/SQL content region outputting the necessary wrapper tags for my Flash movie (which I copied from the FusionCharts examples), pointing it to my uploaded swf file and feeding it the XML from my database function (which I call in "before regions" page process).

How Do I Learn to Ride a Bike if I Don’t Own a Bike? I get it.  A lot of businesses went out and bought the bike.  In fact, some of them bought a bike that would be the envy of a Tour de France cyclist.  Now, they’re trying to learn how to ride it.

Hey, that’s fine.  Smart business people don’t live a linear life.  You get the tools and implement the tools – all while you’re learning the tools. 

There’s no “on button” for Big Data.  You need people who will put their hands into it, manipulate it and find the valuable insights.